Overview

Dataset statistics

Number of variables15
Number of observations99003
Missing cells177
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.3 MiB
Average record size in memory120.0 B

Variable types

Numeric14
Categorical1

Alerts

age is highly overall correlated with dob_yearHigh correlation
dob_year is highly overall correlated with ageHigh correlation
friend_count is highly overall correlated with friendships_initiated and 3 other fieldsHigh correlation
friendships_initiated is highly overall correlated with friend_count and 2 other fieldsHigh correlation
likes is highly overall correlated with likes_received and 4 other fieldsHigh correlation
likes_received is highly overall correlated with friend_count and 5 other fieldsHigh correlation
mobile_likes is highly overall correlated with likes and 3 other fieldsHigh correlation
mobile_likes_received is highly overall correlated with friend_count and 5 other fieldsHigh correlation
www_likes is highly overall correlated with likes and 1 other fieldsHigh correlation
www_likes_received is highly overall correlated with friend_count and 5 other fieldsHigh correlation
likes_received is highly skewed (γ1 = 112.0745682)Skewed
mobile_likes_received is highly skewed (γ1 = 107.5312999)Skewed
www_likes_received is highly skewed (γ1 = 126.257317)Skewed
userid has unique valuesUnique
friend_count has 1962 (2.0%) zerosZeros
friendships_initiated has 2997 (3.0%) zerosZeros
likes has 22308 (22.5%) zerosZeros
likes_received has 24428 (24.7%) zerosZeros
mobile_likes has 35056 (35.4%) zerosZeros
mobile_likes_received has 30003 (30.3%) zerosZeros
www_likes has 60999 (61.6%) zerosZeros
www_likes_received has 36864 (37.2%) zerosZeros

Reproduction

Analysis started2023-08-01 00:56:48.214410
Analysis finished2023-08-01 00:57:05.604330
Duration17.39 seconds
Software versionydata-profiling vv4.3.2
Download configurationconfig.json

Variables

userid
Real number (ℝ)

UNIQUE 

Distinct99003
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1597045.2
Minimum1000008
Maximum2193542
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size773.6 KiB
2023-08-01T06:27:05.658676image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1000008
5-th percentile1060618.3
Q11298805.5
median1596148
Q31895744
95-th percentile2133357.1
Maximum2193542
Range1193534
Interquartile range (IQR)596938.5

Descriptive statistics

Standard deviation344059.18
Coefficient of variation (CV)0.21543484
Kurtosis-1.1995568
Mean1597045.2
Median Absolute Deviation (MAD)298438
Skewness0.00010766057
Sum1.5811227 × 1011
Variance1.1837672 × 1011
MonotonicityNot monotonic
2023-08-01T06:27:05.748381image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2094382 1
 
< 0.1%
1096160 1
 
< 0.1%
2095762 1
 
< 0.1%
1910322 1
 
< 0.1%
1787699 1
 
< 0.1%
1191101 1
 
< 0.1%
1569326 1
 
< 0.1%
1077005 1
 
< 0.1%
1935412 1
 
< 0.1%
1827911 1
 
< 0.1%
Other values (98993) 98993
> 99.9%
ValueCountFrequency (%)
1000008 1
< 0.1%
1000013 1
< 0.1%
1000015 1
< 0.1%
1000038 1
< 0.1%
1000059 1
< 0.1%
1000061 1
< 0.1%
1000068 1
< 0.1%
1000094 1
< 0.1%
1000103 1
< 0.1%
1000125 1
< 0.1%
ValueCountFrequency (%)
2193542 1
< 0.1%
2193538 1
< 0.1%
2193522 1
< 0.1%
2193499 1
< 0.1%
2193485 1
< 0.1%
2193473 1
< 0.1%
2193468 1
< 0.1%
2193465 1
< 0.1%
2193460 1
< 0.1%
2193418 1
< 0.1%

age
Real number (ℝ)

HIGH CORRELATION 

Distinct101
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.280224
Minimum13
Maximum113
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size773.6 KiB
2023-08-01T06:27:05.832587image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile15
Q120
median28
Q350
95-th percentile90
Maximum113
Range100
Interquartile range (IQR)30

Descriptive statistics

Standard deviation22.589748
Coefficient of variation (CV)0.60594455
Kurtosis1.5614468
Mean37.280224
Median Absolute Deviation (MAD)10
Skewness1.4152607
Sum3690854
Variance510.29673
MonotonicityNot monotonic
2023-08-01T06:27:05.910053image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
18 5196
 
5.2%
23 4404
 
4.4%
19 4391
 
4.4%
20 3769
 
3.8%
21 3671
 
3.7%
25 3641
 
3.7%
17 3283
 
3.3%
16 3086
 
3.1%
22 3032
 
3.1%
24 2827
 
2.9%
Other values (91) 61703
62.3%
ValueCountFrequency (%)
13 484
 
0.5%
14 1925
 
1.9%
15 2618
2.6%
16 3086
3.1%
17 3283
3.3%
18 5196
5.2%
19 4391
4.4%
20 3769
3.8%
21 3671
3.7%
22 3032
3.1%
ValueCountFrequency (%)
113 202
 
0.2%
112 18
 
< 0.1%
111 18
 
< 0.1%
110 15
 
< 0.1%
109 9
 
< 0.1%
108 1661
1.7%
107 98
 
0.1%
106 125
 
0.1%
105 80
 
0.1%
104 73
 
0.1%

dob_day
Real number (ℝ)

Distinct31
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean14.530408
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size773.6 KiB
2023-08-01T06:27:05.981893image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q17
median14
Q322
95-th percentile29
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation9.0156064
Coefficient of variation (CV)0.62046477
Kurtosis-1.1889601
Mean14.530408
Median Absolute Deviation (MAD)8
Skewness0.10784076
Sum1438554
Variance81.281158
MonotonicityNot monotonic
2023-08-01T06:27:06.047800image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1 7900
 
8.0%
10 4030
 
4.1%
15 3555
 
3.6%
5 3545
 
3.6%
12 3413
 
3.4%
2 3409
 
3.4%
3 3291
 
3.3%
17 3266
 
3.3%
20 3263
 
3.3%
14 3219
 
3.3%
Other values (21) 60112
60.7%
ValueCountFrequency (%)
1 7900
8.0%
2 3409
3.4%
3 3291
3.3%
4 3217
3.2%
5 3545
3.6%
6 3108
 
3.1%
7 3010
 
3.0%
8 3202
3.2%
9 3003
 
3.0%
10 4030
4.1%
ValueCountFrequency (%)
31 1507
1.5%
30 2530
2.6%
29 2508
2.5%
28 2955
3.0%
27 2755
2.8%
26 2753
2.8%
25 3217
3.2%
24 2807
2.8%
23 2864
2.9%
22 2838
2.9%

dob_year
Real number (ℝ)

HIGH CORRELATION 

Distinct101
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1975.7198
Minimum1900
Maximum2000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size773.6 KiB
2023-08-01T06:27:06.127807image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1900
5-th percentile1923
Q11963
median1985
Q31993
95-th percentile1998
Maximum2000
Range100
Interquartile range (IQR)30

Descriptive statistics

Standard deviation22.589748
Coefficient of variation (CV)0.01143368
Kurtosis1.5614468
Mean1975.7198
Median Absolute Deviation (MAD)10
Skewness-1.4152607
Sum1.9560218 × 108
Variance510.29673
MonotonicityNot monotonic
2023-08-01T06:27:06.209842image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1995 5196
 
5.2%
1990 4404
 
4.4%
1994 4391
 
4.4%
1993 3769
 
3.8%
1992 3671
 
3.7%
1988 3641
 
3.7%
1996 3283
 
3.3%
1997 3086
 
3.1%
1991 3032
 
3.1%
1989 2827
 
2.9%
Other values (91) 61703
62.3%
ValueCountFrequency (%)
1900 202
 
0.2%
1901 18
 
< 0.1%
1902 18
 
< 0.1%
1903 15
 
< 0.1%
1904 9
 
< 0.1%
1905 1661
1.7%
1906 98
 
0.1%
1907 125
 
0.1%
1908 80
 
0.1%
1909 73
 
0.1%
ValueCountFrequency (%)
2000 484
 
0.5%
1999 1925
 
1.9%
1998 2618
2.6%
1997 3086
3.1%
1996 3283
3.3%
1995 5196
5.2%
1994 4391
4.4%
1993 3769
3.8%
1992 3671
3.7%
1991 3032
3.1%

dob_month
Real number (ℝ)

Distinct12
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.2833652
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size773.6 KiB
2023-08-01T06:27:06.279283image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median6
Q39
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.5296716
Coefficient of variation (CV)0.5617486
Kurtosis-1.2403976
Mean6.2833652
Median Absolute Deviation (MAD)3
Skewness0.031295507
Sum622072
Variance12.458581
MonotonicityNot monotonic
2023-08-01T06:27:06.338507image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
1 11772
11.9%
10 8476
8.6%
5 8271
8.4%
8 8266
8.3%
3 8110
8.2%
7 8021
8.1%
9 7939
8.0%
12 7894
8.0%
4 7810
7.9%
2 7632
7.7%
Other values (2) 14812
15.0%
ValueCountFrequency (%)
1 11772
11.9%
2 7632
7.7%
3 8110
8.2%
4 7810
7.9%
5 8271
8.4%
6 7607
7.7%
7 8021
8.1%
8 8266
8.3%
9 7939
8.0%
10 8476
8.6%
ValueCountFrequency (%)
12 7894
8.0%
11 7205
7.3%
10 8476
8.6%
9 7939
8.0%
8 8266
8.3%
7 8021
8.1%
6 7607
7.7%
5 8271
8.4%
4 7810
7.9%
3 8110
8.2%

gender
Categorical

Distinct2
Distinct (%)< 0.1%
Missing175
Missing (%)0.2%
Memory size773.6 KiB
male
58574 
female
40254 

Length

Max length6
Median length4
Mean length4.8146274
Min length4

Characters and Unicode

Total characters475820
Distinct characters5
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowmale
2nd rowfemale
3rd rowmale
4th rowfemale
5th rowmale

Common Values

ValueCountFrequency (%)
male 58574
59.2%
female 40254
40.7%
(Missing) 175
 
0.2%

Length

2023-08-01T06:27:06.408623image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-08-01T06:27:06.494036image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
ValueCountFrequency (%)
male 58574
59.3%
female 40254
40.7%

Most occurring characters

ValueCountFrequency (%)
e 139082
29.2%
m 98828
20.8%
a 98828
20.8%
l 98828
20.8%
f 40254
 
8.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 475820
100.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 139082
29.2%
m 98828
20.8%
a 98828
20.8%
l 98828
20.8%
f 40254
 
8.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 475820
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 139082
29.2%
m 98828
20.8%
a 98828
20.8%
l 98828
20.8%
f 40254
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 475820
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 139082
29.2%
m 98828
20.8%
a 98828
20.8%
l 98828
20.8%
f 40254
 
8.5%

tenure
Real number (ℝ)

Distinct2426
Distinct (%)2.5%
Missing2
Missing (%)< 0.1%
Infinite0
Infinite (%)0.0%
Mean537.88737
Minimum0
Maximum3139
Zeros70
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size773.6 KiB
2023-08-01T06:27:06.556136image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile47
Q1226
median412
Q3675
95-th percentile1575
Maximum3139
Range3139
Interquartile range (IQR)449

Descriptive statistics

Standard deviation457.64987
Coefficient of variation (CV)0.85082844
Kurtosis2.1990583
Mean537.88737
Median Absolute Deviation (MAD)213
Skewness1.5356809
Sum53251388
Variance209443.41
MonotonicityNot monotonic
2023-08-01T06:27:06.632819image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
300 173
 
0.2%
303 170
 
0.2%
242 164
 
0.2%
272 163
 
0.2%
257 161
 
0.2%
297 161
 
0.2%
280 160
 
0.2%
285 160
 
0.2%
284 158
 
0.2%
278 158
 
0.2%
Other values (2416) 97373
98.4%
ValueCountFrequency (%)
0 70
0.1%
1 60
0.1%
2 72
0.1%
3 79
0.1%
4 86
0.1%
5 92
0.1%
6 93
0.1%
7 84
0.1%
8 87
0.1%
9 93
0.1%
ValueCountFrequency (%)
3139 3
< 0.1%
3129 1
 
< 0.1%
3128 1
 
< 0.1%
3101 1
 
< 0.1%
3019 1
 
< 0.1%
2958 1
 
< 0.1%
2926 1
 
< 0.1%
2888 1
 
< 0.1%
2822 1
 
< 0.1%
2788 1
 
< 0.1%

friend_count
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct2562
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean196.35079
Minimum0
Maximum4923
Zeros1962
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size773.6 KiB
2023-08-01T06:27:06.713516image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3
Q131
median82
Q3206
95-th percentile720
Maximum4923
Range4923
Interquartile range (IQR)175

Descriptive statistics

Standard deviation387.30423
Coefficient of variation (CV)1.9725117
Kurtosis50.094273
Mean196.35079
Median Absolute Deviation (MAD)64
Skewness6.0590085
Sum19439317
Variance150004.57
MonotonicityNot monotonic
2023-08-01T06:27:06.794366image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1962
 
2.0%
1 1816
 
1.8%
2 1117
 
1.1%
3 860
 
0.9%
5 789
 
0.8%
4 749
 
0.8%
10 737
 
0.7%
24 732
 
0.7%
6 720
 
0.7%
29 719
 
0.7%
Other values (2552) 88802
89.7%
ValueCountFrequency (%)
0 1962
2.0%
1 1816
1.8%
2 1117
1.1%
3 860
0.9%
4 749
 
0.8%
5 789
0.8%
6 720
 
0.7%
7 671
 
0.7%
8 718
 
0.7%
9 700
 
0.7%
ValueCountFrequency (%)
4923 1
< 0.1%
4917 1
< 0.1%
4863 1
< 0.1%
4845 1
< 0.1%
4844 1
< 0.1%
4826 1
< 0.1%
4817 1
< 0.1%
4803 1
< 0.1%
4797 1
< 0.1%
4794 1
< 0.1%

friendships_initiated
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1519
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean107.45247
Minimum0
Maximum4144
Zeros2997
Zeros (%)3.0%
Negative0
Negative (%)0.0%
Memory size773.6 KiB
2023-08-01T06:27:06.875320image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q117
median46
Q3117
95-th percentile418
Maximum4144
Range4144
Interquartile range (IQR)100

Descriptive statistics

Standard deviation188.78695
Coefficient of variation (CV)1.7569345
Kurtosis42.535601
Mean107.45247
Median Absolute Deviation (MAD)36
Skewness5.1507574
Sum10638117
Variance35640.513
MonotonicityNot monotonic
2023-08-01T06:27:06.952049image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2997
 
3.0%
1 2212
 
2.2%
2 1551
 
1.6%
3 1355
 
1.4%
4 1352
 
1.4%
5 1328
 
1.3%
6 1328
 
1.3%
11 1319
 
1.3%
8 1314
 
1.3%
13 1279
 
1.3%
Other values (1509) 82968
83.8%
ValueCountFrequency (%)
0 2997
3.0%
1 2212
2.2%
2 1551
1.6%
3 1355
1.4%
4 1352
1.4%
5 1328
1.3%
6 1328
1.3%
7 1237
1.2%
8 1314
1.3%
9 1245
1.3%
ValueCountFrequency (%)
4144 1
< 0.1%
3654 1
< 0.1%
3594 1
< 0.1%
3538 1
< 0.1%
3415 1
< 0.1%
3238 1
< 0.1%
3233 1
< 0.1%
3086 1
< 0.1%
3078 1
< 0.1%
3024 1
< 0.1%

likes
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct2924
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean156.07879
Minimum0
Maximum25111
Zeros22308
Zeros (%)22.5%
Negative0
Negative (%)0.0%
Memory size773.6 KiB
2023-08-01T06:27:07.029329image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median11
Q381
95-th percentile726
Maximum25111
Range25111
Interquartile range (IQR)80

Descriptive statistics

Standard deviation572.28068
Coefficient of variation (CV)3.6666141
Kurtosis200.44569
Mean156.07879
Median Absolute Deviation (MAD)11
Skewness11.023704
Sum15452268
Variance327505.18
MonotonicityNot monotonic
2023-08-01T06:27:07.108996image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 22308
22.5%
1 6928
 
7.0%
2 4434
 
4.5%
3 3240
 
3.3%
4 2507
 
2.5%
5 2027
 
2.0%
6 1806
 
1.8%
7 1618
 
1.6%
8 1430
 
1.4%
9 1381
 
1.4%
Other values (2914) 51324
51.8%
ValueCountFrequency (%)
0 22308
22.5%
1 6928
 
7.0%
2 4434
 
4.5%
3 3240
 
3.3%
4 2507
 
2.5%
5 2027
 
2.0%
6 1806
 
1.8%
7 1618
 
1.6%
8 1430
 
1.4%
9 1381
 
1.4%
ValueCountFrequency (%)
25111 1
< 0.1%
21652 1
< 0.1%
16732 1
< 0.1%
16583 1
< 0.1%
14799 1
< 0.1%
14355 1
< 0.1%
14050 1
< 0.1%
14039 1
< 0.1%
13692 1
< 0.1%
13622 1
< 0.1%

likes_received
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct2681
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean142.68936
Minimum0
Maximum261197
Zeros24428
Zeros (%)24.7%
Negative0
Negative (%)0.0%
Memory size773.6 KiB
2023-08-01T06:27:07.187377image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median8
Q359
95-th percentile561
Maximum261197
Range261197
Interquartile range (IQR)58

Descriptive statistics

Standard deviation1387.9196
Coefficient of variation (CV)9.7268611
Kurtosis17384.94
Mean142.68936
Median Absolute Deviation (MAD)8
Skewness112.07457
Sum14126675
Variance1926320.9
MonotonicityNot monotonic
2023-08-01T06:27:07.271741image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 24428
24.7%
1 7305
 
7.4%
2 4541
 
4.6%
3 3347
 
3.4%
4 2669
 
2.7%
5 2373
 
2.4%
6 1873
 
1.9%
7 1680
 
1.7%
8 1538
 
1.6%
9 1351
 
1.4%
Other values (2671) 47898
48.4%
ValueCountFrequency (%)
0 24428
24.7%
1 7305
 
7.4%
2 4541
 
4.6%
3 3347
 
3.4%
4 2669
 
2.7%
5 2373
 
2.4%
6 1873
 
1.9%
7 1680
 
1.7%
8 1538
 
1.6%
9 1351
 
1.4%
ValueCountFrequency (%)
261197 1
< 0.1%
178166 1
< 0.1%
152014 1
< 0.1%
106025 1
< 0.1%
82623 1
< 0.1%
53534 1
< 0.1%
52964 1
< 0.1%
45633 1
< 0.1%
42449 1
< 0.1%
39536 1
< 0.1%

mobile_likes
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct2396
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean106.1163
Minimum0
Maximum25111
Zeros35056
Zeros (%)35.4%
Negative0
Negative (%)0.0%
Memory size773.6 KiB
2023-08-01T06:27:07.351062image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q346
95-th percentile481.9
Maximum25111
Range25111
Interquartile range (IQR)46

Descriptive statistics

Standard deviation445.25299
Coefficient of variation (CV)4.1958963
Kurtosis360.98858
Mean106.1163
Median Absolute Deviation (MAD)4
Skewness14.161237
Sum10505832
Variance198250.22
MonotonicityNot monotonic
2023-08-01T06:27:07.431868image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 35056
35.4%
1 6297
 
6.4%
2 3941
 
4.0%
3 2917
 
2.9%
4 2265
 
2.3%
5 1794
 
1.8%
6 1598
 
1.6%
7 1395
 
1.4%
8 1212
 
1.2%
9 1149
 
1.2%
Other values (2386) 41379
41.8%
ValueCountFrequency (%)
0 35056
35.4%
1 6297
 
6.4%
2 3941
 
4.0%
3 2917
 
2.9%
4 2265
 
2.3%
5 1794
 
1.8%
6 1598
 
1.6%
7 1395
 
1.4%
8 1212
 
1.2%
9 1149
 
1.2%
ValueCountFrequency (%)
25111 1
< 0.1%
21652 1
< 0.1%
16732 1
< 0.1%
14039 1
< 0.1%
13529 1
< 0.1%
12934 1
< 0.1%
12639 1
< 0.1%
12104 1
< 0.1%
12083 1
< 0.1%
11959 1
< 0.1%

mobile_likes_received
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct2004
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean84.120491
Minimum0
Maximum138561
Zeros30003
Zeros (%)30.3%
Negative0
Negative (%)0.0%
Memory size773.6 KiB
2023-08-01T06:27:07.710630image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4
Q333
95-th percentile317
Maximum138561
Range138561
Interquartile range (IQR)33

Descriptive statistics

Standard deviation839.88944
Coefficient of variation (CV)9.9843621
Kurtosis15522.649
Mean84.120491
Median Absolute Deviation (MAD)4
Skewness107.5313
Sum8328181
Variance705414.28
MonotonicityNot monotonic
2023-08-01T06:27:07.787527image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 30003
30.3%
1 8243
 
8.3%
2 4948
 
5.0%
3 3608
 
3.6%
4 2944
 
3.0%
5 2383
 
2.4%
6 2022
 
2.0%
7 1745
 
1.8%
8 1521
 
1.5%
9 1437
 
1.5%
Other values (1994) 40149
40.6%
ValueCountFrequency (%)
0 30003
30.3%
1 8243
 
8.3%
2 4948
 
5.0%
3 3608
 
3.6%
4 2944
 
3.0%
5 2383
 
2.4%
6 2022
 
2.0%
7 1745
 
1.8%
8 1521
 
1.5%
9 1437
 
1.5%
ValueCountFrequency (%)
138561 1
< 0.1%
131244 1
< 0.1%
89911 1
< 0.1%
73333 1
< 0.1%
43410 1
< 0.1%
30754 1
< 0.1%
30387 1
< 0.1%
27353 1
< 0.1%
20770 1
< 0.1%
18925 1
< 0.1%

www_likes
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct1726
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean49.962425
Minimum0
Maximum14865
Zeros60999
Zeros (%)61.6%
Negative0
Negative (%)0.0%
Memory size773.6 KiB
2023-08-01T06:27:07.871805image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q37
95-th percentile208
Maximum14865
Range14865
Interquartile range (IQR)7

Descriptive statistics

Standard deviation285.56015
Coefficient of variation (CV)5.7154982
Kurtosis449.14848
Mean49.962425
Median Absolute Deviation (MAD)0
Skewness16.911025
Sum4946430
Variance81544.6
MonotonicityNot monotonic
2023-08-01T06:27:07.950117image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 60999
61.6%
1 4697
 
4.7%
2 2760
 
2.8%
3 1948
 
2.0%
4 1419
 
1.4%
5 1202
 
1.2%
6 1081
 
1.1%
7 897
 
0.9%
8 792
 
0.8%
9 757
 
0.8%
Other values (1716) 22451
 
22.7%
ValueCountFrequency (%)
0 60999
61.6%
1 4697
 
4.7%
2 2760
 
2.8%
3 1948
 
2.0%
4 1419
 
1.4%
5 1202
 
1.2%
6 1081
 
1.1%
7 897
 
0.9%
8 792
 
0.8%
9 757
 
0.8%
ValueCountFrequency (%)
14865 1
< 0.1%
12903 1
< 0.1%
11077 1
< 0.1%
10763 1
< 0.1%
10627 1
< 0.1%
10539 1
< 0.1%
10255 1
< 0.1%
10232 1
< 0.1%
9902 1
< 0.1%
9431 1
< 0.1%

www_likes_received
Real number (ℝ)

HIGH CORRELATION  SKEWED  ZEROS 

Distinct1636
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58.568831
Minimum0
Maximum129953
Zeros36864
Zeros (%)37.2%
Negative0
Negative (%)0.0%
Memory size773.6 KiB
2023-08-01T06:27:08.033146image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q320
95-th percentile227
Maximum129953
Range129953
Interquartile range (IQR)20

Descriptive statistics

Standard deviation601.41635
Coefficient of variation (CV)10.268539
Kurtosis23812.249
Mean58.568831
Median Absolute Deviation (MAD)2
Skewness126.25732
Sum5798490
Variance361701.62
MonotonicityNot monotonic
2023-08-01T06:27:08.115703image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 36864
37.2%
1 8513
 
8.6%
2 5111
 
5.2%
3 3586
 
3.6%
4 2828
 
2.9%
5 2317
 
2.3%
6 1918
 
1.9%
7 1602
 
1.6%
8 1445
 
1.5%
9 1373
 
1.4%
Other values (1626) 33446
33.8%
ValueCountFrequency (%)
0 36864
37.2%
1 8513
 
8.6%
2 5111
 
5.2%
3 3586
 
3.6%
4 2828
 
2.9%
5 2317
 
2.3%
6 1918
 
1.9%
7 1602
 
1.6%
8 1445
 
1.5%
9 1373
 
1.4%
ValueCountFrequency (%)
129953 1
< 0.1%
62103 1
< 0.1%
39605 1
< 0.1%
39213 1
< 0.1%
34039 1
< 0.1%
32692 1
< 0.1%
29337 1
< 0.1%
23147 1
< 0.1%
22644 1
< 0.1%
15096 1
< 0.1%

Interactions

2023-08-01T06:27:04.081131image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:50.087456image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:51.177566image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:52.271487image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:53.324036image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:54.418736image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:55.576653image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:56.641487image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:57.641394image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:58.761929image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:59.756919image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:00.767881image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:01.808044image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:02.874323image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:04.157611image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:50.185000image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:51.252360image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:52.348011image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:53.411371image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:54.496182image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:55.654971image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:56.722280image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:57.719360image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:58.834088image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:59.830888image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:00.848784image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:01.889925image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:03.116418image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:04.228447image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:50.258531image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:51.320377image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:52.418170image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:53.490696image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:54.564244image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:55.736209image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:56.789830image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:57.788708image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:58.900344image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:59.896808image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:00.922061image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:01.964692image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:03.187511image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:04.303884image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:50.338613image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:51.396870image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:52.491070image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:53.576412image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:54.637616image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:55.811804image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:56.860062image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:57.862464image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:58.971152image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:59.968059image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:01.001557image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:02.043329image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:03.262884image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:04.376555image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:50.417675image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:51.472499image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:52.564522image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:53.657083image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:54.710230image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:55.886221image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:56.930487image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:57.933912image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:59.044189image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:00.040393image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:01.078177image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:02.119288image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:03.339191image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:04.450491image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:50.495696image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:51.547298image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:52.637102image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:53.739736image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:54.783968image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:55.960448image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:56.999806image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:58.005748image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:59.112800image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:00.115517image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:01.151558image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:02.193197image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:03.411852image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:04.523931image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:50.572894image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:51.619392image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:52.712802image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:53.814584image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:54.859964image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:56.034689image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:57.070404image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:58.077642image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:59.186014image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:00.191075image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:01.224603image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:02.270558image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:03.487282image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:04.596552image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:50.647470image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:51.688393image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:52.786291image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:53.886876image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:54.935602image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:56.109939image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:57.137394image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:58.144564image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:59.256014image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:00.264016image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:01.296162image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:02.344362image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:03.559848image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:04.668120image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:50.723181image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:51.756588image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:52.856784image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:53.956297image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:55.118477image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:56.181466image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:57.203521image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:58.211232image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:59.324394image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:00.333958image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:01.367321image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:02.416147image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:03.632418image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:04.739503image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:50.796663image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:51.825304image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:52.929004image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:54.030689image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:55.192825image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:56.253338image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:57.274119image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:58.279134image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:59.394611image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:00.403632image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:01.437455image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:02.491307image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:03.704411image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:04.810704image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:50.872219image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:51.894490image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:53.002139image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:54.104284image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:55.267191image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:56.332830image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:57.344003image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:58.348346image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:59.463587image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:00.472611image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:01.508133image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:02.565277image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:03.777583image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:04.884069image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:50.944333image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:51.964458image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:53.074750image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:54.180626image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:55.340910image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:56.406749image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:57.417557image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:58.415797image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:59.534375image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:00.542197image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:01.579506image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:02.640449image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:03.851214image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:04.960526image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:51.023165image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:52.123538image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:53.155620image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:54.260362image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:55.419618image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:56.485971image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:57.491226image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:58.617311image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:59.610091image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:00.617598image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:01.657332image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:02.719505image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:03.928926image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:05.042394image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:51.100544image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:52.197656image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:53.239354image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:54.340407image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:55.500017image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:56.564912image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:57.565519image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:58.689759image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:26:59.685768image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:00.694575image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:01.732459image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:02.797436image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
2023-08-01T06:27:04.005993image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/

Correlations

2023-08-01T06:27:08.188987image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
useridagedob_daydob_yeardob_monthtenurefriend_countfriendships_initiatedlikeslikes_receivedmobile_likesmobile_likes_receivedwww_likeswww_likes_receivedgender
userid1.000-0.007-0.0010.0070.0030.0000.0030.0030.0020.0010.0020.0010.000-0.0010.004
age-0.0071.0000.034-1.0000.0290.341-0.162-0.1820.0360.024-0.0690.0060.0780.0410.136
dob_day-0.0010.0341.000-0.0340.1360.0530.0510.0440.0430.0440.0300.0400.0370.0440.051
dob_year0.007-1.000-0.0341.000-0.029-0.3410.1620.182-0.036-0.0240.069-0.006-0.078-0.0410.137
dob_month0.0030.0290.136-0.0291.0000.0360.0420.0370.0310.0380.0260.0380.0250.0360.045
tenure0.0000.3410.053-0.3410.0361.0000.3090.2300.1420.1730.0770.1620.1910.1800.093
friend_count0.003-0.1620.0510.1620.0420.3091.0000.9460.4680.5530.4360.5480.2730.5070.084
friendships_initiated0.003-0.1820.0440.1820.0370.2300.9461.0000.4490.5150.4190.5100.2600.4700.019
likes0.0020.0360.043-0.0360.0310.1420.4680.4491.0000.8090.8340.7840.5480.7550.060
likes_received0.0010.0240.044-0.0240.0380.1730.5530.5150.8091.0000.6970.9650.4610.9240.009
mobile_likes0.002-0.0690.0300.0690.0260.0770.4360.4190.8340.6971.0000.7300.1710.5910.042
mobile_likes_received0.0010.0060.040-0.0060.0380.1620.5480.5100.7840.9650.7301.0000.3760.8260.006
www_likes0.0000.0780.037-0.0780.0250.1910.2730.2600.5480.4610.1710.3761.0000.5410.052
www_likes_received-0.0010.0410.044-0.0410.0360.1800.5070.4700.7550.9240.5910.8260.5411.0000.005
gender0.0040.1360.0510.1370.0450.0930.0840.0190.0600.0090.0420.0060.0520.0051.000

Missing values

2023-08-01T06:27:05.152452image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
A simple visualization of nullity by column.
2023-08-01T06:27:05.343303image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2023-08-01T06:27:05.546721image/svg+xmlMatplotlib v3.7.1, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

useridagedob_daydob_yeardob_monthgendertenurefriend_countfriendships_initiatedlikeslikes_receivedmobile_likesmobile_likes_receivedwww_likeswww_likes_received
020943821419199911male266.000000000
11192601142199911female6.000000000
220838841416199911male13.000000000
312031681425199912female93.000000000
41733186144199912male82.000000000
51524765141199912male15.000000000
61136133131420001male12.000000000
7168036113420001female0.000000000
8136517413120001male81.000000000
9171256713220002male171.000000000
useridagedob_daydob_yeardob_monthgendertenurefriend_countfriendships_initiatedlikeslikes_receivedmobile_likesmobile_likes_receivedwww_likeswww_likes_received
989931654565191519948male394.04538414445011508844355961669127
98994206300620419931female402.01988332735110602572487333310332692
989951132164209199310female699.03611973450777684414690993859
989961668695242519894female182.0293812726018177655843117081756057
9899714589852814198512female290.022181618462610268429042503366018
98998126829968419454female541.021183413996180893505118874916202
989991256153181219953female21.01968172044011341243991059222820
990001195943151019985female111.0200215241195912554119591146201092
990011468023231119904female416.0256018545066516450657600756
990021397896391519745female397.020497689410124439410953002913